Principal Data Engineer

Microsoft • ,

1d • $142,800 - $304,200 • Hybrid

About The Position

MCAPS-Core Data & Applied AI (DAAI) is a centralized data and AI organization that advances Microsoft's transformation through enterprise data platforms, advanced analytics, AI-powered solutions, automation, and governance. The Principal Data Engineer will build AI-powered platforms, intelligent agents, and data foundations using software engineering, data engineering, and AI expertise. The role focuses on scalable solutions involving generative AI, LLMs, agentic workflows, and enterprise data platforms, translating data into actionable business impact.

The position leads development of cloud-native applications, APIs, and platform services; architects AI platforms and applications; creates AI-ready data platforms, knowledge systems, and orchestration frameworks; and guides technical strategy for Applied AI. It also establishes reusable frameworks and practices for responsible AI, governance, security, reliability, and operational excellence, while providing hands-on technical leadership and partnering across engineering, data science, product, business, and technology teams.

Candidates who live within 50 miles of Microsoft's Redmond campus are required to work in the office three days per week. The role requires passing the Microsoft Cloud Background Check upon hire or transfer and every two years thereafter.

Requirements

• Master's degree in Computer Science, Math, Software Engineering, Computer Engineering, or a related field and 4+ years of experience in business analytics, data science, software development, data modeling, or data engineering; OR bachelor's degree in one of those fields and 6+ years of relevant experience; OR equivalent experience.
• Ability to meet Microsoft, customer, and/or government security screening requirements, including passing the Microsoft Cloud Background Check upon hire or transfer and every two years thereafter.

Nice To Haves

• Master's degree in Computer Science, Math, Software Engineering, Computer Engineering, or a related field and 8+ years of relevant experience; OR bachelor's degree in one of those fields and 12+ years of relevant experience; OR equivalent experience.
• 3+ years of experience working with data governance, compliance, and/or data security.
• 5+ years working in data-intensive Azure environments, translating business requirements into scalable data and AI solutions using technologies such as Microsoft Fabric, Azure AI Foundry, Azure Data Platform, Synapse Analytics, and Azure App Service.
• Proficiency developing solutions with Python and/or modern programming languages such as C#, Java, Scala, or equivalent.
• Demonstrated ability to design and implement generative AI and enterprise AI solutions, including LLMs, RAG, semantic search, vector databases, Copilots, intelligent agents, and multi-agent systems.
• Knowledge of AI platform engineering and production AI practices, including LLM orchestration, knowledge graphs, prompt engineering, model tuning, evaluation frameworks, MLOps/LLMOps, observability, and model governance.
• Background leading enterprise-scale cloud, data, analytics, and AI transformation initiatives, including architecture decisions, engineering strategy, and cross-functional execution.
• Ability to develop cloud-scale services using modern software engineering and SRE practices while mentoring engineers, fostering innovation, and advancing engineering practices across complex organizations.

Responsibilities

• Lead end-to-end development of cloud-native applications, APIs, and platform services across frontend, backend, integration, security, observability, testing, and continuous delivery.
• Architect and deliver AI platforms, copilots, agentic systems, and intelligent applications using generative AI, LLMs, and advanced reasoning capabilities.
• Design and build AI-ready data platforms, knowledge systems, scalable AI services, APIs, and orchestration frameworks for autonomous agents, intelligent automation, and enterprise workflows.
• Drive technical strategy and architecture for Applied AI solutions in partnership with engineering, data science, product, and business teams.
• Create reusable AI frameworks, SDKs, and platform services that improve developer productivity, model performance, scalability, governance, and reliability.
• Establish best practices for Responsible AI, AI governance, model evaluation, security, compliance, observability, and operational excellence.
• Provide hands-on technical leadership through architecture and code reviews, mentoring, and direct contributions to software, data, and AI solutions.
• Partner with business and technology leaders to identify and deliver AI opportunities that improve productivity, decision-making, and customer experiences.
• Turn emerging AI technologies into scalable platforms, reusable services, and enterprise-wide solutions.
• Embody Microsoft's culture and values.

Benefits

• The role may be eligible for benefits and other compensation; additional benefits and pay information is available through Microsoft's careers website.

What This Job Offers

• Job Type: Full-time
• Career Level: Principal